IDS Presentation given to CUNY Libraries by Kevin Reiss in April, 2011.

2. Who’s Currently Using IDS Search?

3. IDS Statistics 34 Million volumes with roughly 60 active libraries (Will be closer to 40 Million by the end of the Year)

4. 2010 IDS Statistics For 9/1/2010 – 12/31/2010 Borrowing Volume– 89,000+ total ILL requests 53,000 of these requests filled within member libraries (60%) Article Borrowing requests; 55% delivered to user within 24 Hours; 78% delivered within 48 hours

5. Why IDS Search? The IDS Search Team set out to develop a discovery tool with the following three goals: Use data from Worldcat to seach both local and IDS-wide collections simultaneously Enhance resource sharing within the IDS Project Provide a simple and powerful user experience.

6. IDS Search increases resource sharing Impact at SUNY Oswego and SUNY Buffalo State: 68% increase at Oswego in a 1 year period (3,593 to 6,071) 95% increase at Buff State in a 6 mo. period (526 to 1024)

7. IDS Search Under the Hood Open URL IDS Search Interface ILL system Yahoo Spell Check Result Facets IDS Search Application Google Books Preview Item Availability In JSON or XML Worldcat Result Set in Marcxml Related Subjects Worldcat Search API IDS Search Availability Service z39.50 Server OCLC Bibliographic Data OCLC Holdings Data ILS Database

8. The complex family of technologies behind IDS Search provide a tool that is simple and easy to use.

9. IDS Search Core Functions Searches Worldcat Bibliographic and Holdings data Real time circulation status check in local library ILS system (Aleph, Voyager, Innovative) Link search results directly to ILL Request System via OpenURL

10. IDS Search User Friendly Features Search Scoping (My Library, IDS, Worldwide) Citation Tools Spell check RSS feeds Search limits (format, language, etc.) Autosearch Google Books Previews Custom Contextual links to other seach tools

11. The IDS Search interface is simple and elegant with progressive disclosure of features at the point of need.

12. IDS Search promotes both local collections and resource sharing.

13. The “Find in” features takes searches from IDS Search into local collections, vendor databases, and web resources.

14. If searches do not return results, IDS Search automatically expands the search using the Autosearch Feature.

15. The spell check feature lets users know they have misspelled a word and provides an easy way to search again with the correct word.

16. “Cite This” provides citations for major citation styles.

17. Google Books Previews are linked and embedded throughout results.

18. IDS Search has undergone extensive usability testing in its development process. IDS Search was beta tested in 2009 by several libraries, with extensive feedback sessions from librarians and staff. IDS Search was tested in 2009 and 2010 by a usability team at University of Rochester. In 2010, researchers at SUNY Geneseo conducted usability testing using eye tracking software and eye movement miscue analysis (EMMA). Further eye tracking studies are planned for April 2011.

19. IDS Search usability studies are using advanced equipment and techniques. Photographs by William Jones III

20. IDS Search’s default interface has been heavily tested and refined using multiple methods. Photographs by William Jones III

21. Eye Tracking studies focus on important features of IDS Search such as Google Preview.

22. Usability tests and user input have led to continuous interface improvements.

25. The Dashboard will create custom search boxes that you can copy and paste into library webpages to promote your catalog.

26. Easily customize what features of IDS Search you use and how they work.

27. Customization Examples: Oswego

28. Customization Examples: Brockport

29. Customization Examples: TC3

30. Easy to run reports provide graphs and tables on how much IDS Search is used.

31. All user input into IDS Search is recorded and presented in an easy to understand format that can be shared with all staff.

32. Reports such as the hourly usage report which identifies high and low use times offer built in analysis tools.

33. The IDS search development team regularly incorporates feedback into the development process. Examples include: Custom library groups Custom Links to other search tools (local catalog, databases, etc.) Custom search limiters What features do you need?

38. Learn More about IDS Search IDS Search Blog http://idssearch.wordpress.com/ IDS Search Site http://idsproject.org/Tools/IDSSearch.aspx IDS Search Listserv http://mail.geneseo.edu/mailman/listinfo/idssearch-l

39. The IDS Search team is made up of developers, public services librarians, and administrators from across SUNY, CUNY, and IDS. Mike Curtis (Manager) – SUNY Upstate Medical Nathan Fixler – SUNY Office of Library and Information Services Mike Mulligan – SUNY Upstate Medical Cyril Oberlander – SUNY Geneseo Shannon Pritting – SUNY Oswego Kevin Reiss – CUNY Office of Library Services Ed Rivenburgh – IDS Project Director Adam Traub – Rochester Institute of Technology